async def update(self, record: Record): db = self.parent.db # Store feature data feature_cols = self.parent.FEATURE_COLS feature_data = OrderedDict.fromkeys(feature_cols) feature_data.update(record.features(feature_cols)) await db.execute( "INSERT OR REPLACE INTO features (key, " + ", ".join(feature_cols) + ") " "VALUES(?, " + ", ".join("?" * len(feature_cols)) + ")", [record.key] + list(feature_data.values()), ) # Store prediction try: prediction = record.prediction("target_name") prediction_cols = self.parent.PREDICTION_COLS prediction_data = OrderedDict.fromkeys(prediction_cols) prediction_data.update(prediction.dict()) await db.execute( "INSERT OR REPLACE INTO prediction (key, " + ", ".join(prediction_cols) + ") " "VALUES(?, " + ", ".join("?" * len(prediction_cols)) + ")", [record.key] + list(prediction_data.values()), ) except KeyError: pass
async def test_predict(self): records: Dict[str, Record] = { record.key: record.export() async for record in self.sctx.records() } async with self.post(f"/model/{self.mlabel}/predict/0", json=records) as r: i: int = 0 response = await r.json() for key, record_data in response["records"].items(): record = Record(key, data=record_data) self.assertEqual(int(record.key), i) self.assertEqual( record.feature("by_ten"), record.prediction("Salary").value / 10, ) self.assertEqual(float(record.key), record.prediction("Salary").confidence) i += 1 self.assertEqual(i, self.num_records)
class TestRecord(unittest.TestCase): def setUp(self): self.null = Record("null") self.full = Record( "full", data=dict( features=dict(dead="beef"), extra=dict(extra="read all about it"), ), extra=dict(half=True), ) def test_dict(self): data = self.full.dict() self.assertIn("extra", data) def test_repr(self): repr(self.full) def test_str(self): self.full.prediction = RecordPrediction() self.assertIn("Undetermined", str(self.full)) self.full.data.prediction = { "Prediction": RecordPrediction(value="Good") } self.assertIn("Good", str(self.full)) self.full.extra.update(dict(hi=5)) self.assertIn("5", str(self.full)) self.full.extra = dict() self.assertNotIn("5", str(self.full)) def test_merge(self): null = Record("null") null.merge(self.full) self.assertIn("half", null.extra) self.assertTrue(null.extra["half"]) def test_key(self): return self.full.data.key def test_evaluated(self): old_last_updated = self.full.data.last_updated results = {"new": "feature"} self.full.evaluated({"feed": "face"}) self.assertIn("feed", self.full.data.features) self.assertEqual("face", self.full.data.features["feed"]) self.full.evaluated(results, overwrite=True) self.assertEqual(self.full.data.features, results) self.assertLessEqual(old_last_updated, self.full.data.last_updated) def test_features(self): self.assertIn("dead", self.full.features()) self.assertIn("dead", self.full.features(["dead"])) self.assertFalse(self.full.features(["dead", "beaf"])) def test_predicted(self): old_prediction = self.full.data.prediction.copy() old_last_updated = self.full.data.last_updated self.full.predicted("target_name", "feed", 1.00) self.assertNotEqual(old_prediction, self.full.data.prediction) self.assertLessEqual(old_last_updated, self.full.data.last_updated) def test_prediction(self): self.full.predicted("target_name", "feed", 1.00) self.assertTrue(self.full.prediction("target_name"))